This question came up when I was looking up the last year in the playoffs for seven probable NFC playoff teams. Both New Orleans and Philadelphia last played in the playoffs four years ago, in 2013. And then the thought came up in my head, “But Drew Brees is a veteran QB.” This seems intuitive, but wanting to actually create such a definition and then later to test this using a logistic regression, there is the rub.

There are any number of QBs a fan can point to and see that the QB mattered. Roger Staubach seemed a veteran in this context back in the 1970s, Joe Montana in the 1980s, Ben Roethlisberger in the 21st century, Eli Manning in 2011, and Aaron Rogers last year. But plenty of questions abound. If a veteran QB is an independent variable whose presence or absence changes the odds of winning a playoff game, what tools do we use to define such a person? What tools would we use to eliminate entanglement, in this case between the team’s overall offensive strength and the QB himself?

The difference between a good metric and a bad metric can be seen when looking at the effect of the running game on winning. The correlation between rushing yards per carry and winning is pretty small. The correlation between run success rate and winning are larger. In short, being able to reliably make it on 3rd and 1 contributes more to success than running 5 yards a carry as opposed to 4.

At this point I’m just discussing the idea. With a definition in mind, we can do one independent variable logistic regression tests. Then with a big enough data set – 15 years of playoff data should be enough, we can start testing three independent variable logistic models (QB + SOS + PPX).

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Best wishes for Ryan Shazier after his horrible accident last night.

For those of you interested in predictive stats, you might want to read up on ESPN’s FPI, which is a predictive stat and considers, among other things, previous seasons. In that it’s similar to my playoff formula, as my formula takes into account previous playoff experience. I don’t know the whole of what is in FPI, as it’s a classic proprietary stat. But it’s worth keeping ears open, and listening to how ESPN has evolved the metric.

This post will give data for a two week span. Week 12 and also week 13. Week 12 will be on top.

In Week 12, it looked as if Philadelphia was firming up a grip on #1 in a variety of metrics. Their loss in week 13 has made searching for “the best” the same kind of mad mix it was earlier in the season.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
176        94     53.4      28.06        16.19     11.86

Calculated Pythagorean Exponent:  2.65

Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PHI     13.0    11  10   1   0  90.9  83.4  13.13  14.55 -1.41
2     NE       8.0    11   9   2   0  81.8  73.8   9.28   9.55 -0.27
3     MIN      8.0    11   9   2   0  81.8  70.5   8.95   6.91  2.04
4     PIT      5.0    11   9   2   0  81.8  68.3   5.12   5.91 -0.79
5     NO       9.0    11   8   3   0  72.7  72.8  10.98   9.09  1.89
6     LA       6.0    11   8   3   0  72.7  77.6  10.85  11.18 -0.33
7     CAR      3.0    11   8   3   0  72.7  61.8   4.48   3.73  0.75
8     JAX     12.0    11   7   4   0  63.6  77.7   7.17   9.18 -2.01
9     ATL      4.0    11   7   4   0  63.6  59.3   2.72   3.18 -0.46
10    SEA      3.0    11   7   4   0  63.6  64.6   1.96   4.91 -2.95
11    TEN      3.0    11   7   4   0  63.6  43.0  -5.73  -2.45 -3.27
12    KC       7.0    11   6   5   0  54.5  59.3   4.19   3.27  0.92
13    BAL      7.0    11   6   5   0  54.5  65.0   2.83   4.45 -1.63
14    DET      3.0    11   6   5   0  54.5  57.1   3.97   2.73  1.24
15    BUF      3.0    11   6   5   0  54.5  40.2  -3.48  -3.27 -0.21
16    OAK     -1.0    11   5   6   0  45.5  40.3  -4.59  -3.27 -1.32
17    LAC     -2.0    11   5   6   0  45.5  63.5   3.79   4.27 -0.48
18    WAS     -3.0    11   5   6   0  45.5  45.5   2.17  -1.64  3.81
19    GB      -3.0    11   5   6   0  45.5  42.3  -0.30  -2.64  2.33
20    CIN     -3.0    11   5   6   0  45.5  44.9  -4.71  -1.45 -3.26
21    DAL     -4.0    11   5   6   0  45.5  44.4  -1.28  -2.00  0.72
22    ARI     -6.0    11   5   6   0  45.5  30.3  -6.49  -6.82  0.33
23    HOU     -3.0    11   4   7   0  36.4  49.5  -0.48  -0.18 -0.30
24    NYJ     -5.0    11   4   7   0  36.4  42.1  -4.59  -2.64 -1.95
25    TB      -5.0    11   4   7   0  36.4  39.5  -3.25  -3.55  0.29
26    MIA    -10.0    11   4   7   0  36.4  20.7  -9.42 -10.45  1.03
27    IND     -3.0    11   3   8   0  27.3  24.2 -11.19  -9.55 -1.65
28    CHI     -6.0    11   3   8   0  27.3  28.2  -2.43  -6.82  4.39
29    DEN    -10.0    11   3   8   0  27.3  28.2  -6.75  -7.55  0.79
30    NYG    -10.0    11   2   9   0  18.2  23.8  -6.80  -8.64  1.83
31    SF      -3.0    11   1  10   0   9.1  24.8  -8.61  -8.82  0.21
32    CLE    -14.0    11   0  11   0   0.0  18.7 -11.49 -11.18 -0.31

Week 13 data:

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
192       105     54.7      28.01        16.08     11.93

Calculated Pythagorean Exponent:  2.66


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     NE      12.0    12  10   2   0  83.3  76.6   9.70  10.42 -0.71
2     PHI     11.5    12  10   2   0  83.3  79.9  10.21  12.17 -1.96
3     MIN      8.0    12  10   2   0  83.3  70.9   8.57   6.75  1.82
4     PIT      4.0    12  10   2   0  83.3  67.7   4.91   5.67 -0.76
5     NO       9.5    12   9   3   0  75.0  73.0  10.98   9.17  1.81
6     LA       8.0    12   9   3   0  75.0  78.5  10.76  11.58 -0.82
7     JAX     14.0    12   8   4   0  66.7  79.9   7.97  10.08 -2.12
8     SEA      4.5    12   8   4   0  66.7  67.1   3.83   5.67 -1.84
9     TEN      3.5    12   8   4   0  66.7  46.1  -3.53  -1.33 -2.20
10    CAR      3.0    12   8   4   0  66.7  58.1   4.14   2.58  1.56
11    BAL     10.0    12   7   5   0  58.3  69.1   5.30   6.08 -0.79
12    ATL      3.5    12   7   5   0  58.3  57.7   3.18   2.50  0.68
13    DAL      3.5    12   6   6   0  50.0  50.5  -0.15   0.17 -0.32
14    KC       3.0    12   6   6   0  50.0  56.7   2.17   2.42 -0.25
15    DET      0.0    12   6   6   0  50.0  51.3   1.98   0.50  1.48
16    GB       0.0    12   6   6   0  50.0  44.3   0.18  -1.92  2.10
17    OAK      0.0    12   6   6   0  50.0  42.7  -4.47  -2.42 -2.05
18    LAC     -0.5    12   6   6   0  50.0  65.1   2.77   4.67 -1.89
19    BUF     -0.5    12   6   6   0  50.0  35.7  -4.15  -4.67  0.52
20    CIN     -3.0    12   5   7   0  41.7  44.5  -3.78  -1.58 -2.20
21    NYJ     -4.0    12   5   7   0  41.7  44.7  -2.89  -1.83 -1.05
22    WAS     -5.5    12   5   7   0  41.7  40.6  -0.53  -3.50  2.97
23    MIA     -6.5    12   5   7   0  41.7  28.0  -6.62  -7.42  0.80
24    ARI     -8.0    12   5   7   0  41.7  28.4  -6.41  -7.58  1.18
25    HOU     -4.5    12   4   8   0  33.3  47.1  -0.96  -1.08  0.12
26    TB      -5.0    12   4   8   0  33.3  38.9  -3.29  -3.75  0.46
27    IND     -3.5    12   3   9   0  25.0  22.0 -10.54 -10.42 -0.12
28    CHI     -4.5    12   3   9   0  25.0  29.1  -3.16  -6.33  3.18
29    DEN    -10.0    12   3   9   0  25.0  24.4  -9.42  -9.08 -0.34
30    SF      -3.0    12   2  10   0  16.7  26.2  -8.20  -8.00 -0.20
31    NYG     -8.5    12   2  10   0  16.7  24.1  -8.03  -8.50  0.47
32    CLE    -13.0    12   0  12   0   0.0  18.4 -10.50 -11.00  0.50

It’s been a harder work week than usual, and really haven’t had time to touch on the stats this week. I don’t have many comments at the moment. Kansas City is in a mid season swoon. Washington played well. I wish it had a better result, but Drew Brees is a comeback king. Minnesota looks like a tough opponent. New England has sneaked into the top five of a number of scoring stats. I caught the very end of the Atlanta Seattle game. It was probably one I should have watched.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
160        84     52.5      28.17        16.17     12.00

Calculated Pythagorean Exponent:  2.60


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PHI     11.5    10   9   1   0  90.0  80.0  11.69  13.20 -1.51
2     NO      11.5    10   8   2   0  80.0  75.5  11.68  10.60  1.08
3     MIN      9.0    10   8   2   0  80.0  70.6   9.21   6.90  2.31
4     NE       7.5    10   8   2   0  80.0  71.7   9.28   8.70  0.58
5     PIT      5.5    10   8   2   0  80.0  69.6   5.96   6.20 -0.24
6     JAX     14.0    10   7   3   0  70.0  80.8   8.81  10.40 -1.59
7     LA       7.5    10   7   3   0  70.0  78.1  10.35  11.70 -1.35
8     CAR      3.0    10   7   3   0  70.0  60.8   4.46   3.30  1.16
9     KC       7.5    10   6   4   0  60.0  61.2   5.39   4.20  1.19
10    DET      5.0    10   6   4   0  60.0  59.4   4.39   3.70  0.69
11    ATL      3.5    10   6   4   0  60.0  56.2   2.00   2.10 -0.10
12    SEA      3.0    10   6   4   0  60.0  62.5   1.66   4.30 -2.64
13    TEN      3.0    10   6   4   0  60.0  41.6  -5.35  -3.10 -2.25
14    BAL      5.0    10   5   5   0  50.0  63.9   2.90   4.20 -1.30
15    DAL      3.5    10   5   5   0  50.0  50.0   0.04   0.00  0.04
16    BUF     -0.5    10   5   5   0  50.0  38.3  -5.16  -4.20 -0.96
17    GB      -3.0    10   5   5   0  50.0  42.3  -0.11  -2.60  2.49
18    LAC     -2.0    10   4   6   0  40.0  57.8   1.95   2.50 -0.55
19    HOU     -3.0    10   4   6   0  40.0  51.2   0.02   0.50 -0.48
20    OAK     -3.5    10   4   6   0  40.0  37.8  -5.35  -4.30 -1.05
21    CIN     -3.5    10   4   6   0  40.0  39.5  -5.14  -3.00 -2.14
22    TB      -4.0    10   4   6   0  40.0  42.5  -2.60  -2.50 -0.10
23    NYJ     -4.0    10   4   6   0  40.0  43.6  -4.90  -2.10 -2.80
24    WAS     -5.5    10   4   6   0  40.0  42.8   1.93  -2.80  4.73
25    MIA     -6.5    10   4   6   0  40.0  22.2  -9.71  -9.70 -0.01
26    ARI     -8.0    10   4   6   0  40.0  27.8  -8.17  -7.80 -0.37
27    IND     -3.0    10   3   7   0  30.0  23.8 -11.23 -10.10 -1.13
28    CHI     -4.5    10   3   7   0  30.0  34.9  -0.92  -4.70  3.78
29    DEN    -10.0    10   3   7   0  30.0  28.8  -6.81  -7.60  0.79
30    NYG     -7.5    10   2   8   0  20.0  25.0  -6.80  -8.50  1.70
31    SF      -3.0    10   1   9   0  10.0  26.0  -9.02  -8.60 -0.42
32    CLE    -13.0    10   0  10   0   0.0  19.4 -10.43 -10.90  0.47

It is getting to the point now where games won and lost become important. In the NFC, at least, teams leading the division have very high probabilities of making the playoffs. Team with 5 and 6 wins are, as of the moment, on the outside looking in, with a possibility of making the playoffs.

Before the Dallas Atlanta game I would have said that Dallas was the better bet as a playoff team, but Dallas’s inability to remain healthy was central to the 27-7 Falcons win. And that will remain their critical issue. Ezekiel Elliot has a workable replacement in Alfred Morris, but there is no functional replacement for the injured Tyron Smith.

While the revitalized New Orleans Saints are having a season on offense comparable to last years, their improvement on defense is substantial. Their DSRS last year was about -5.73 points, while now it is 4.84 points. That’s a turnaround of 10.57 points. In terms of the Rams, it’s about a 18 point improvement in the offense and a 4 point improvement in the defense. Philadelphia by contrast, has improved by 9 points on offense, while the defense isn’t as good as last year, by about 3 and a half points.

The best defense of the year and the best team in the AFC, by the numbers, is that of Jacksonville. Many years of accumulating talent appears to have borne fruit. The only issue with Jacksonville is that they have been erratic. No one is sure which Jacksonville team will appear.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
146        78     53.4      28.01        16.18     11.83

Calculated Pythagorean Exponent:  2.78


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PHI     10.0     9   8   1   0  88.9  78.2   9.41  11.56 -2.15
2     NO      14.0     9   7   2   0  77.8  79.4  12.53  11.44  1.08
3     LA      10.0     9   7   2   0  77.8  84.3  12.64  14.89 -2.25
4     MIN      8.0     9   7   2   0  77.8  68.2   6.75   5.78  0.97
5     NE       7.0     9   7   2   0  77.8  68.3   8.09   6.89  1.20
6     PIT      5.0     9   7   2   0  77.8  65.7   4.12   4.33 -0.21
7     CAR      3.0    10   7   3   0  70.0  61.5   4.49   3.30  1.19
8     JAX     16.0     9   6   3   0  66.7  81.1   9.32  10.22 -0.90
9     KC       8.0     9   6   3   0  66.7  63.3   6.48   5.00  1.48
10    SEA      3.0     9   6   3   0  66.7  66.5   2.49   5.11 -2.62
11    TEN      3.0     9   6   3   0  66.7  47.3  -4.12  -0.89 -3.23
12    DAL     11.0     9   5   4   0  55.6  58.8   2.35   3.11 -0.77
13    DET      7.0     9   5   4   0  55.6  60.3   4.30   3.78  0.52
14    ATL      4.0     9   5   4   0  55.6  56.6   2.45   2.00  0.45
15    GB       3.0     9   5   4   0  55.6  49.0   2.24  -0.33  2.57
16    BUF      3.0     9   5   4   0  55.6  45.6  -2.30  -1.33 -0.97
17    OAK     -1.0     9   4   5   0  44.4  43.9  -4.23  -2.00 -2.23
18    BAL     -3.0     9   4   5   0  44.4  57.3   0.36   2.11 -1.76
19    MIA     -3.0     9   4   5   0  44.4  20.3  -9.46  -9.67  0.20
20    ARI     -6.0     9   4   5   0  44.4  26.7  -7.60  -7.56 -0.05
21    WAS     -8.0     9   4   5   0  44.4  42.1   1.28  -2.78  4.05
22    NYJ     -4.0    10   4   6   0  40.0  43.1  -4.37  -2.10 -2.27
23    LAC     -2.0     9   3   6   0  33.3  47.9  -0.89  -0.56 -0.34
24    HOU     -3.0     9   3   6   0  33.3  48.5   0.23  -0.56  0.79
25    CIN     -4.0     9   3   6   0  33.3  36.4  -5.10  -3.67 -1.43
26    TB      -5.0     9   3   6   0  33.3  37.5  -3.03  -3.89  0.86
27    CHI     -6.0     9   3   6   0  33.3  32.8  -1.32  -4.89  3.57
28    DEN    -10.0     9   3   6   0  33.3  26.6  -7.06  -8.11  1.05
29    IND     -3.0    10   3   7   0  30.0  22.4 -10.96 -10.10 -0.86
30    NYG    -10.0     9   1   8   0  11.1  21.7  -8.51  -9.78  1.27
31    SF      -3.0    10   1   9   0  10.0  24.6  -8.80  -8.60 -0.20
32    CLE    -14.0     9   0   9   0   0.0  19.1 -11.75 -10.78 -0.98

Scott Kacsmar is making Eagles fans angry again, by pointing out how many of Carson Wentz’s TD passes start on drives where the ball is inside the opponents 20 yard line. This kind of short TD drive is weighted accurately in EPA based stats, but inflates standard scoring models, such as ANYA and the NFL passer rating. That doesn’t change the fact that Carson Wentz has been in the top five of the ESPN QBR for a while now. For that matter, all three of the top 2016 quarterbacks are in the ESPN QBR top ten.

Ezekiel Elliott has a court date on Thursday afternoon and Friday is a Federal Holiday. Zeke is eligible to play at least until the court makes a decision. The odds the decision is made Thursday is very small. He’s likely to play Atlanta.

I wish I had seen the Washington comeback against the Seahawks. I was away from the screen at the time.

So how many seasons has it been now that Atlanta plays its best for one half? This was true in the late Mike Smith era, and continues to this day.

Best teams? For now, 1a and 1b are Jacksonville and the Rams. Third are the Eagles. Fourth is New Orleans. Fifth is Kansas City, I suspect, but at this point, reasonable arguments could be made for Minnesota, New England, and Pittsburgh.
 

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
132        70     53.0      27.77        16.14     11.63

Calculated Pythagorean Exponent:  2.55


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PHI     10.0     9   8   1   0  88.9  76.3   9.50  11.56 -2.05
2     NO      11.5     8   6   2   0  75.0  71.2   8.70   8.25  0.45
3     MIN      9.0     8   6   2   0  75.0  67.2   5.76   5.50  0.26
4     LA       7.5     8   6   2   0  75.0  79.4  11.25  13.50 -2.25
5     NE       6.0     8   6   2   0  75.0  61.7   6.05   4.62  1.43
6     PIT      5.5     8   6   2   0  75.0  65.0   5.84   4.50  1.34
7     KC       8.0     9   6   3   0  66.7  62.2   7.37   5.00  2.37
8     CAR      3.0     9   6   3   0  66.7  53.5   2.23   1.00  1.23
9     JAX     18.5     8   5   3   0  62.5  80.9  10.72  11.12 -0.40
10    DAL     11.0     8   5   3   0  62.5  64.8   4.85   6.00 -1.15
11    BUF      4.5     8   5   3   0  62.5  59.8   0.50   3.12 -2.63
12    SEA      3.0     8   5   3   0  62.5  64.7   2.87   5.00 -2.13
13    TEN      3.0     8   5   3   0  62.5  45.9  -3.85  -1.50 -2.35
14    DET      2.0     8   4   4   0  50.0  56.5   3.45   2.50  0.95
15    ATL      0.5     8   4   4   0  50.0  49.3  -0.33  -0.25 -0.08
16    MIA     -0.5     8   4   4   0  50.0  24.9  -8.55  -7.88 -0.68
17    GB      -3.0     8   4   4   0  50.0  46.6   1.15  -1.25  2.40
18    WAS     -3.5     8   4   4   0  50.0  44.2   1.85  -2.12  3.98
19    ARI     -4.0     8   4   4   0  50.0  28.1  -8.77  -7.75 -1.02
20    OAK     -1.0     9   4   5   0  44.4  44.4  -3.20  -2.00 -1.20
21    NYJ     -3.0     9   4   5   0  44.4  44.9  -3.37  -1.78 -1.59
22    BAL     -3.0     9   4   5   0  44.4  56.7   0.91   2.11 -1.20
23    LAC     -2.0     8   3   5   0  37.5  49.2  -0.91  -0.25 -0.66
24    HOU     -3.0     8   3   5   0  37.5  56.1   2.08   2.62 -0.55
25    CIN     -3.5     8   3   5   0  37.5  37.4  -3.93  -3.62 -0.30
26    CHI     -4.5     8   3   5   0  37.5  34.9  -2.13  -4.62  2.49
27    DEN    -10.0     8   3   5   0  37.5  33.0  -4.73  -6.00  1.27
28    IND     -3.0     9   3   6   0  33.3  23.0 -12.16 -10.89 -1.27
29    TB      -5.0     8   2   6   0  25.0  36.0  -4.33  -5.00  0.67
30    NYG     -9.5     8   1   7   0  12.5  23.1  -7.01  -9.75  2.74
31    SF      -3.0     9   0   9   0   0.0  21.3 -10.35 -10.67  0.32
32    CLE     -8.5     8   0   8   0   0.0  20.6 -11.47 -10.38 -1.09

There is an interesting tweet by Aaron Schatz in that not a single team has exceeded 30% DVOA this year. None did in 2016 either. This indicates we’re in a season with a lot of pretty good teams and not one great team. That’s my feeling as well. There isn’t a team as well rounded as the Patriots were last year. Most good teams have a better offense than defense.

The 49ers have traded for a NE quarterback, Jimmy Garoppolo. Eagles have traded for a running back, Jay Ajayi. Ezekiel Elliot’s situation looks grim. Dallas fans are complaining that the NY judge had a conflict of interest (her husband appears to have worked for the NFL) that she ignored.

There is a great World Series in play, and it’s hard not to at least mention baseball. Games 2 and 5 were simply insane.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
119        63     52.9      27.66        16.13     11.53

Calculated Pythagorean Exponent:  2.62


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PHI      7.5     8   7   1   0  87.5  73.9   7.67   9.50 -1.83
2     MIN      9.0     8   6   2   0  75.0  67.7   6.07   5.50  0.57
3     KC       8.5     8   6   2   0  75.0  67.0   9.91   7.00  2.91
4     NE       6.0     8   6   2   0  75.0  62.1   6.86   4.62  2.24
5     PIT      5.5     8   6   2   0  75.0  65.4   6.18   4.50  1.68
6     NO       9.0     7   5   2   0  71.4  67.3   7.82   6.57  1.25
7     BUF      6.0     7   5   2   0  71.4  67.9   3.73   5.43 -1.70
8     LA       5.0     7   5   2   0  71.4  75.5   7.21  10.57 -3.37
9     SEA      3.0     7   5   2   0  71.4  67.7   3.01   6.14 -3.13
10    CAR      3.0     8   5   3   0  62.5  52.7   2.28   0.75  1.53
11    JAX     21.0     7   4   3   0  57.1  79.1   9.66  10.43 -0.77
12    DAL     11.0     7   4   3   0  57.1  63.2   2.55   5.29 -2.74
13    ATL      4.0     7   4   3   0  57.1  50.4   0.00   0.14 -0.14
14    GB       3.0     7   4   3   0  57.1  51.2   2.56   0.43  2.13
15    TEN      3.0     7   4   3   0  57.1  44.1  -5.11  -2.14 -2.97
16    MIA      2.0     7   4   3   0  57.1  21.2  -9.28  -8.57 -0.71
17    BAL      5.0     8   4   4   0  50.0  59.0   2.06   2.75 -0.69
18    HOU     -3.0     7   3   4   0  42.9  58.7   5.26   3.86  1.40
19    DET     -3.0     7   3   4   0  42.9  52.7   1.84   1.00  0.84
20    CIN     -3.0     7   3   4   0  42.9  43.4  -2.95  -1.86 -1.09
21    WAS     -9.0     7   3   4   0  42.9  42.4   0.23  -2.86  3.09
22    DEN    -10.0     7   3   4   0  42.9  40.5  -1.36  -2.86  1.49
23    ARI    -11.0     7   3   4   0  42.9  22.5 -11.81 -10.29 -1.52
24    LAC     -2.0     8   3   5   0  37.5  49.1   0.47  -0.25  0.72
25    OAK     -3.5     8   3   5   0  37.5  42.4  -2.02  -2.62  0.60
26    NYJ     -4.0     8   3   5   0  37.5  39.1  -5.11  -3.62 -1.49
27    CHI     -4.5     8   3   5   0  37.5  34.6  -1.59  -4.62  3.03
28    TB      -5.0     7   2   5   0  28.6  41.8  -2.73  -2.86  0.13
29    IND     -8.5     8   2   6   0  25.0  19.2 -15.86 -13.00 -2.86
30    NYG     -5.0     7   1   6   0  14.3  29.6  -4.65  -6.29  1.63
31    SF      -3.0     8   0   8   0   0.0  21.3 -11.34 -10.75 -0.59
32    CLE     -8.5     8   0   8   0   0.0  20.0 -11.56 -10.38 -1.18

One of the problems with having a record breaking offense powered by the best season of a good QBs career is just how much of that season was a product of luck. Luck is a major factor in NFL play; just ask the Green Bay Packers. But for some, in particular Atlanta Falcon’s fans, the game against New England was supposed to be the reincarnation of the 2016 offense. Instead, they were almost completely shut down, scoring only late in the game.
So, are the Philadelphia Eagles lucky? A little bit. Multiply a Pythagorean of 0.687 by 7 and you get 4.8 wins. That said they are the only 6 win team this far into the season, with a collection of stats that put them in the top five of the league regardless.
Top five candidates? Kansas City of course qualifies. So does New Orleans and Jacksonville. The last might be the Rams. How much of their success will continue into the second half of the season is anyone’s guess. New England will be in the mix by the end of the year, I suspect, but it’s not there now. It’s one of the teams in the top ten, but not top five just yet.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
106        55     51.9      27.56        16.20     11.36

Calculated Pythagorean Exponent:  2.53


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PHI      5.0     7   6   1   0  85.7  68.7   7.83   7.57  0.25
2     KC       8.0     7   5   2   0  71.4  65.4  11.17   6.57  4.60
3     MIN      8.0     7   5   2   0  71.4  62.7   5.40   3.86  1.55
4     PIT      6.0     7   5   2   0  71.4  64.6   5.38   4.43  0.95
5     LA       5.0     7   5   2   0  71.4  74.8   6.43  10.57 -4.14
6     NE       5.0     7   5   2   0  71.4  60.1   7.27   4.14  3.12
7     NO      11.5     6   4   2   0  66.7  65.4   8.59   6.33  2.26
8     SEA      4.5     6   4   2   0  66.7  71.1   1.55   6.67 -5.11
9     BUF      4.5     6   4   2   0  66.7  60.2   1.69   3.00 -1.31
10    MIA      2.5     6   4   2   0  66.7  37.8  -3.39  -3.33 -0.05
11    JAX     21.0     7   4   3   0  57.1  78.4   9.03  10.43 -1.40
12    GB       3.0     7   4   3   0  57.1  51.2   2.04   0.43  1.61
13    TEN      3.0     7   4   3   0  57.1  44.3  -4.42  -2.14 -2.28
14    CAR      3.0     7   4   3   0  57.1  46.3   0.64  -1.14  1.78
15    DAL      3.5     6   3   3   0  50.0  59.4   0.15   3.83 -3.68
16    DET      2.0     6   3   3   0  50.0  54.9   1.60   2.00 -0.40
17    HOU      0.5     6   3   3   0  50.0  61.6   6.48   5.00  1.48
18    ATL      0.5     6   3   3   0  50.0  48.1   0.41  -0.67  1.08
19    WAS     -3.5     6   3   3   0  50.0  47.4   2.67  -1.00  3.67
20    DEN     -3.5     6   3   3   0  50.0  44.4  -1.40  -1.67  0.26
21    OAK     -1.0     7   3   4   0  42.9  49.6   0.50  -0.14  0.64
22    LAC     -2.0     7   3   4   0  42.9  52.8   2.06   0.86  1.20
23    NYJ     -3.0     7   3   4   0  42.9  39.9  -3.48  -3.43 -0.05
24    BAL     -3.0     7   3   4   0  42.9  41.9  -2.08  -2.57  0.49
25    CHI     -3.0     7   3   4   0  42.9  36.8  -2.74  -4.14  1.40
26    ARI    -11.0     7   3   4   0  42.9  23.2 -12.54 -10.29 -2.26
27    CIN     -3.5     6   2   4   0  33.3  41.6  -2.09  -2.33  0.24
28    TB      -4.0     6   2   4   0  33.3  47.4  -1.97  -1.00 -0.97
29    IND    -14.0     7   2   5   0  28.6  17.1 -18.11 -14.71 -3.39
30    NYG     -5.0     7   1   6   0  14.3  30.2  -4.88  -6.29  1.40
31    SF      -3.0     7   0   7   0   0.0  26.0 -11.74  -9.00 -2.74
32    CLE     -3.0     7   0   7   0   0.0  22.2 -12.04  -9.43 -2.62